Biology subjects

Zhou, B.

Publications and source records attributed to Zhou, B..

At least 73 records · Page 4Linked to original sources

bioRxiv2024

Endothelial Immunosuppression in Atherosclerosis : Translational Control by Elavl1/HuR

Atherosclerotic plaques are defined by the accumulation of lipids and immune cells beneath the endothelium of the arterial intima. CD8 T cells are among the most abundant immune cell types in plaque, and conditions linked to their activation correlate with increased levels of cardiovascular disease. As lethal effectors of the immune response, CD8 T cell activation is suppressed at multiple levels. These checkpoints are critical in dampening autoimmune responses, and limiting damage in cardiovascular disease. Endothelial cells are well known for their role in recruiting CD8 T and other hematopoietic cells to low and disturbed flow (LDF) arterial regions that develop plaque, but whether they locally influence CD8 effector functions is unclear. Here, we show that endothelial cells can actively suppress CD8 T cell responses in settings of chronic plaque inflammation, but that this behavior is governed by expression of the RNA-binding protein Embryonic Lethal, Abnormal Vision-Like 1 (Elavl1). In response to immune cell recruitment in plaque, the endothelium dynamically shifts splicing of pre-mRNA and their translation to enhance expression of immune-regulatory proteins including C1q and CD27. This program is immuno-suppressive, and limited by Elavl1. We show this by Cdh5(PAC)-CreERT2-mediated deletion of Elavl1 (ECKO), and analysis of changes in translation by Translating Ribosome Affinity Purification (TRAP). In ECKO mice, the translational shift in chronic inflammation is enhanced, leading to increased ribosomal association of C1q components and other critical regulators of immune response and resulting in a [~]70% reduction in plaque CD8 T cells. CITE-seq analysis of the remaining plaque T cells shows that they exhibit lower levels of markers associated with T cell receptor (TCR) signaling, survival, and activation. To understand whether the immunosuppressive mechanism occurred through failed CD8 recruitment or local modulation of T cell responses, we used a novel in vitro co-culture system to show that ECKO endothelial cells suppress CD8 T cell expansion--even in the presence of wild-type myeloid antigen-presenting cells, antigen-specific CD8 T cells, and antigen. Despite the induction of C1q mRNA by T cell co-culture in both wild-type and ECKO endothelial cells, we find C1q protein abundantly expressed only in co-culture with ECKO cells. Together, our data define a novel immune-suppressive transition in the endothelium, reminiscent of the transition of T cells to T-regs, and demonstrate the regulation of this process by Elavl1.

cell biology↗

bioRxiv2024

MACanalyzeR: scRNA-seq Analysis Tool Reveals PPARγHI Lipid-Associated Macrophages Facilitate Thermogenic Expansion in BAT

Macrophages in brown adipose tissue (BAT) play a complex role in regulating its activity. However, the role of macrophages in regulating BAT activation/deactivation has not yet been comprehensively characterized. To elucidate this, we developed MACanalyzeR, a scRNAseq-based tool specifically designed to explore the macrophage features at molecular and metabolic level. MACanalyzeR was applied in scRNA-seq datasets obtained from BAT with thermogenic loss (db/db mice) and activation (High Fat Diet, HFD). Our computational approach revealed that macrophages accumulating in BAT upon these conditions resemble lipid-associated macrophages (LAMs) with foaming-like features. BAT LAMs also show a significant enrichment of genes associated with mitochondria and lysosomes. Interestingly, LAMs identified in BAT from HFD mice positively correlate with thermogenic genes and exhibit an enrichment in PPAR{gamma} signaling pathway, with an activated mitochondrial metabolism. Cell dynamic strategy, revealed that LAM with high Pparg expression levels (PpargHIGH) progressively accumulate during skeletal muscle regeneration, suggesting a potential role for this LAM subcluster in maintaining tissue homeostasis. Our findings suggest PpargHIGH LAMs as a subclass of macrophages potentially contributing in preserving tissue homeostasis associated with high energy demand conditions such as thermogenic and regenerative stimuli.

physiology↗

bioRxiv2024

High-motility pro-tumorigenic monocytes drive macrophage enrichment in the tumor microenvironment

Enrichment of tumor-associated macrophages (TAM{Phi}s) in the tumor microenvironment correlates with worse clinical outcomes in triple-negative breast cancer (TNBC) patients, prompting the development of therapies to inhibit TAM{Phi} infiltration. However, the lackluster efficacy of CCL2-based chemotaxis blockade in clinical trials suggests that a new understanding of monocyte/macrophage infiltration may be necessary. Here we demonstrate that random migration, and not only chemotaxis, drives macrophage tumor infiltration. We identified tumor- associated monocytes (TAMos) that display a dramatically enhanced migration capability, induced rapidly by the tumor microenvironment, that drives effective tumor infiltration, in contrast to low-motility differentiated macrophages. TAMo, not TAM{Phi}, promotes cancer cell proliferation through activation of the MAPK pathway. IL-6 secreted both by cancer cells and TAMo themselves enhances TAMo migration by increasing dendritic protrusion dynamics and myosin- based contractility via the JAK2/STAT3 signaling pathway. Independent from CCL2 mediated chemotaxis, IL-6 driven enhanced migration and pro-proliferative effect of TAMo were validated in a syngeneic TNBC mouse model. Depletion of IL-6 in cancer cells significantly attenuated monocyte infiltration and reversed TAMo-induced cancer cell proliferation. This work reveals the critical role random migration plays in monocyte driven TAM{Phi} enrichment in a tumor and pinpoints IL-6 as a potential therapeutic target in combination with CCL2 to ameliorate current strategies against TAM{Phi} infiltration.

immunology↗

bioRxiv2024

Inclusive, Exclusive and Hierarchical Atlas of NFATc1+/PDGFR-alpha+ Cells in Dental and Periodontal Mesenchyme

Platelet-derived growth factor receptor alpha (PDGFR-) activity is crucial in the process of dental and periodontal mesenchyme regeneration facilitated by autologous platelet concentrates (APCs), such as platelet-rich fibrin (PRF), platelet-rich plasma (PRP) and concentrated growth factors (CGF), as well as by recombinant PDGF drugs. However, it is largely unclear about the physiological patterns and cellular fate determinations of PDGFR-+ cells in the homeostasis maintaining of adult dental and periodontal mesenchyme. We previously identified NFATc1 expressing PDGFR-+ cells as a subtype of skeletal stem cells (SSCs) in limb bone, but their roles in dental and periodontal remain unexplored. To this end, in the present study we investigated the spatiotemporal atlas of NFATc1+ and PDGFR-+ cells residing in dental and periodontal mesenchyme, their capacity for progeny cell generation, and their inclusive, exclusive and hierarchical relations in homeostasis. We utilized CRISPR/Cas9-mediated gene editing to generate two dual recombination systems, which were Cre/loxP-Dre/Rox combined intersectional and exclusive reporters respectively, to concurrently demonstrate the inclusive, exclusive, and hierarchical distributions of NFATc1+ and PDGFR-+ cells and their lineage commitment. By employing the state-of-the-art transgenic lineage tracing techniques in cooperating with tissue clearing-based advanced imaging and three-dimensional slices reconstruction, we systematically mapped the distribution atlas of NFATc1+ and PDGFR-+ cells in dental and periodontal mesenchyme and tracked their in vivo fate trajectories. Our findings extend current understanding of NFATc1+ and PDGFR-+ cells in dental and periodontal mesenchyme homeostasis, and furthermore enhance our comprehension of their sustained therapeutic impact for future clinical investigations.

developmental biology↗

bioRxiv2024

Broken time reversal symmetry in visual motion detection

Our intuition suggests that when a movie is played in reverse, our perception of motion in the reversed movie will be perfectly inverted compared to the original. This intuition is also reflected in many classical theoretical and practical models of motion detection. However, here we demonstrate that this symmetry of motion perception upon time reversal is often broken in real visual systems. In this work, we designed a set of visual stimuli to investigate how stimulus symmetries affect time reversal symmetry breaking in the fruit fly Drosophilas well-studied optomotor rotation behavior. We discovered a suite of new stimuli with a wide variety of different properties that can lead to broken time reversal symmetries in fly behavioral responses. We then trained neural network models to predict the velocity of scenes with both natural and artificial contrast distributions. Training with naturalistic contrast distributions yielded models that break time reversal symmetry, even when the training data was time reversal symmetric. We show analytically and numerically that the breaking of time reversal symmetry in the model responses can arise from contrast asymmetry in the training data, but can also arise from other features of the contrast distribution. Furthermore, shallower neural network models can exhibit stronger symmetry breaking than deeper ones, suggesting that less flexible neural networks promote some forms of time reversal symmetry breaking. Overall, these results reveal a surprising feature of biological motion detectors and suggest that it could arise from constrained optimization in natural environments. SignificanceIn neuroscience, symmetries can tell us about the computations being performed by a circuit. In vision, for instance, one might expect that when a movie is played backward, ones motion percepts should all be reversed. Exact perceptual reversal would indicate a time reversal symmetry, but surprisingly, real visual systems break this symmetry. In this research, we designed visual stimuli to probe different symmetries in motion detection and identify features that lead to symmetry breaking in motion percepts. We discovered that symmetry breaking in motion detection depends strongly on both the detectors architecture and how it is optimized. Interestingly, we find analytically and in simulations that time reversal symmetries are broken in systems optimized to perform with natural inputs.

neuroscience↗

bioRxiv2024

The robust, high-throughput, and temporally regulated roxCre and loxCre reporting systems for genetic modifications in vivo

Cre-loxP technology, a cornerstone in fate mapping and in vivo gene function studies, faces challenges in achieving precise and efficient conditional mutagenesis through inducible systems. This study introduces two innovative genetic tools designed to overcome these limitations. The first, roxCre, enables DreER-mediated Cre release, paving the way for intersectional genetic manipulation that permits increased precision and efficiency. The second, loxCre, facilitates conditional gene targeting by allowing CreER lines to induce Cre expression with significantly enhanced efficiency. These tools incorporate a fluorescent reporter for genetic lineage tracing, simultaneously revealing efficient gene knockout in cells marked by the reporter. These strategies hold great potential for precise and efficient exploration of lineage-specific gene functions, marking a significant advancement in genetic research methodologies.

genetics↗

bioRxiv2024

DeProt: A protein language model with quantizied structure and disentangled attention

Protein language models (PLMs) have shown remarkable capabilities in various protein function prediction tasks. However, while protein function is intricately tied to structure, most existing PLMs do not incorporate protein structure information. To address this issue, we introduce ProSST, a Transformer-based protein language model that seamlessly integrates both protein sequences and structures. ProSST incorporates a structure quantization module and a Transformer architecture with disentangled attention. The structure quantization module translates a 3D protein structure into a sequence of discrete tokens by first serializing the protein structure into residue-level local structures and then embeds them into dense vector space. These vectors are then quantized into discrete structure tokens by a pre-trained clustering model. These tokens serve as an effective protein structure representation. Furthermore, ProSST explicitly learns the relationship between protein residue token sequences and structure token sequences through the sequence-structure disentangled attention. We pre-train ProSST on millions of protein structures using a masked language model objective, enabling it to learn comprehensive contextual representations of proteins. To evaluate the proposed ProSST, we conduct extensive experiments on the zero-shot mutation effect prediction and several supervised downstream tasks, where ProSST achieves the state-of-the-art performance among all baselines. Our code and pretrained models are publicly available 2.

bioinformatics↗

bioRxiv2024

Integrated multiomic analysis identifies TRIP13 as a mediator of alveolar epithelial type II cell dysfunction in idiopathic pulmonary fibrosis

Idiopathic pulmonary fibrosis (IPF) is a lethal progressive lung disease urgently needing new therapies. Current treatments only delay disease progression, leaving lung transplant as the sole remaining option. Recent studies support a model whereby IPF arises because alveolar epithelial type II (AT2) cells, which normally mediate distal lung regeneration, acquire airway and/or mesenchymal characteristics, preventing proper repair. Mechanisms driving this abnormal differentiation remain unclear. We performed integrated transcriptomic and epigenomic analysis of purified AT2 cells which revealed genome-wide alterations in IPF lungs. The most prominent epigenetic alteration was activation of an enhancer in thyroid receptor interactor 13 (TRIP13), coinciding with TRIP13 upregulation. TRIP13 is broadly implicated in epithelial-mesenchymal plasticity and transforming growth factor-{beta} signaling. In cultured human AT2 cells and lung slices, small molecule TRIP inhibitor DCZ0415 prevented acquisition of the mesenchymal gene signature characteristic of IPF, suggesting TRIP13 inhibition as a potential therapeutic approach to fibrotic disease.

bioinformatics↗

bioRxiv2024

A novel functional gene delivery platform based on a commensal human anellovirus demonstrates transduction in multiple tissue types

Anelloviridae is a family of non-enveloped viruses with negative-sense, circular, single-stranded deoxyribonucleic acid (ssDNA) genomes that infect vertebrates and are a ubiquitous component of the human virome. Human anelloviruses evade induction of humoral immune responses and appear to be non-pathogenic. These properties, in conjunction with their enormous genomic diversity and wide tissue distribution, make anelloviruses compelling candidates as vectors for next-generation genetic medicines. Here we report the first gene delivery vector system based on a human commensal virus. This Anellovector is based on a virus of the Betatorquevirus genus. Production is enabled by the development of the Self-Amplifying Trans-complementation of a Universal Recombinant aNellovector (SATURN) system, which relies on a self-replicating plasmid to provide viral proteins in trans that drive replication and capsid-dependent packaging of vector genomes. The SATURN system also utilizes a Cre-lox-based recombination mechanism to generate single unit-sized circular genomes inside the MOLT-4 production cell line. We demonstrate that the SATURN system can package a vector genome from a single betatorquevirus with capsids from multiple betatorquevirus species, supporting the feasibility of establishing a novel vector platform that takes advantage of the remarkable diversity of anelloviruses. The Anellovector demonstrated function in vitro in retinal pigment epithelial (RPE) cells. The Anellovector also demonstrated durable in vivo function in the mouse eye for 9 months after subretinal administration, and achieved comparable gene expression to dose-matched adeno-associated virus 9 (AAV9) when transduced by the intracerebroventricular (ICV) route of administration. To our knowledge, this is the first report of a functional anellovirus-based gene therapy vector. Anellovectors have great potential to deliver safe, redosable, and potent therapeutics, helping to expand the reach of programmable medicines.

bioengineering↗

bioRxiv2024

Development of alcoholic liver disease model for drug evaluation from human induced pluripotent stem cell derived liver organoids

Alcoholic liver disease (ALD) poses a significant health challenge, demanding comprehensive research efforts to enhance our comprehension and treatment strategies. However, the development of effective treatments is hindered by the limitations of existing liver disease models. Liver organoids, characterized by their cellular complexity and three-dimensional (3D) tissue structure closely resembling the human liver, hold promise as ideal models for liver disease research. In this study, we employ a meticulously designed protocol involving the differentiation of human induced pluripotent stem cells (hiPSCs) into liver organoids. This process incorporates a precise combination of cytokines and small molecule compounds within a 3D culture system to guide the differentiation process. Subsequently, these differentiated liver organoids are subjected to ethanol treatment to induce ALD, thus establishing a disease model. Rigorous assessment through a series of experiments reveals that this model partially replicates key pathological features observed in clinical ALD, including cellular mitochondrial damage, elevated cellular reactive oxygen species (ROS) levels, fatty liver, and hepatocyte necrosis. In addition, this model offers potential utility in screening drugs for ALD treatment. Taken together, the liver organoids model of ALD, derived from hiPSCs differentiation, emerges as an invaluable platform for advancing our understanding and management of ALD in clinical settings.

cell biology↗

bioRxiv2024

Interleaved intersectional strategy enables genetic lineage tracing with enhanced specificity

BACKGROUNDDual recombinases have been increasingly employed for enhanced precision in genetic targeting. A recent study utilizing an intersectional genetic approach through dual recombinases (Dre + CreER) has revealed that endocardium-derived fibroblasts (EndoFbs) play a pivotal role in cardiac fibrosis after pressure overload. However, this intersectional strategy has limitations, primarily due to ectopic genetic labeling of non-target cells within the adult heart by the constitutively active Dre recombinase. METHODSTo address this issue, we have developed an advanced, interleaved and intersectional reporter (IIR) strategy in this study. This IIR strategy leverages an inducible CreER to prevent inadvertent Dre-rox recombination during development or disease progression by designing an interleaved reporter to allow for more specific tracing of EndoFbs. Moreover, our IIR system also incorporates Diphtheria Toxin Receptor (DTR) in targeted cells, enabling functional characterization of these cells after genetic ablation. RESULTSEndoFbs were regionally distributed in the heart during homeostasis and proliferated preferentially in response to pressure overload, leading to cardiac fibrosis in defined regions. The IIR strategy enables the tracing of EndoFbs with a more prominent regional pattern and facilitates genetic ablation of EndoFbs through DT injection. In addition, we have applied this IIR strategy to specifically target fibroblasts derived from the epicardium (EpiFbs). Genetic lineage tracing of EpiFb reveals that their distribution pattern is complementary to that of EndoFbs in the adult heart. When a substantial number of EpiFbs were genetically ablated, EndoFbs could replace the loss of EpiFbs in some specific regions of hearts. CONCLUSIONSThe IIR strategy refines the precision of genetic lineage tracing while still employing the constitutively active Dre recombinase in tandem with inducible Cre. EndoFbs and EpiFbs are complementary in their distribution pattern in the heart, where EndoFbs have the potential to replace the loss of EpiFbs in some regions.

genetics↗

bioRxiv2024

Ilamycins are dual inhibitors of ClpX and ClpC1 involved in proteostasis in Mycobacteria

The mycobacterial caseinolytic protease (Clp) system has been recognized as a promising therapeutic target. In this study, we identified two novel ilamycin analogs, ilamycin E (ILE) and ilamycin F (ILF), both targeting the ClpC1 component of the ClpC1P1P2 proteasome. ILE potently disrupts ClpC1P1P2-mediated proteolysis, leading to delayed bactericidal activity, while ILF also binds ClpC1, albeit with lower affinity. Notably, we discovered a unique mutation in clpX and a novel insertion in clpC1, both conferring resistance to ILE and ILF in mycobacterium, validated by gene editing. Furthermore, ILE can also inhibit the proteolytic activity of ClpXP1P2 in a manner dependent on the substrates tag sequence and adaptor. This first demonstration of clpX- and clpC1-mediated ilamycin resistance underscores the potential of ilamycins to target multiple components of the Clp protease system, offering a novel dual-target strategy for combating mycobacterial infections.

microbiology↗

bioRxiv2024

From Sight to Insight: A Multi-task Approach with the Visual Language Decoding Model

Visual neural decoding aims to unlock the mysteries of how the human brain interprets the visual world. While early studies made some progress in decoding visual activity for singular type of information, they failed to concurrently reveal the multi-level interweaving linguistic information in the brain. Here, we developed a novel Visual Language Decoding Model (VLDM) capable of decoding categories, semantic labels, and textual descriptions from visual perceptual activities simultaneously. We selected the large-scale NSD dataset to ensure the efficiency of the decoding model in joint training and evaluation across multiple tasks. For category decoding, we achieved the effective classification of 12 categories with an accuracy of nearly 70%, significantly surpassing the chance level. For label decoding, we attained the precise prediction of 80 specific semantic labels with a 16-fold improvement over the chance level. For text decoding, the scores of the decoded text surpassed the corresponding baseline levels by remarkable margins on six evaluation metrics. This study contributes significantly to extensive applications in multi-layered brain-computer interfaces, potentially leading to more natural and efficient human-computer interaction experiences.

neuroscience↗

bioRxiv2024

Oligomeric HIV-1 Integrase Structures Reveal Functional Plasticity for Intasome Assembly and RNA Binding

Integrase (IN) performs dual essential roles during HIV-1 replication. During ingress, IN functions within an oligomeric "intasome" assembly to catalyze viral DNA integration into host chromatin. During late stages of infection, tetrameric IN binds viral RNA and orchestrates the condensation of ribonucleoprotein complexes into the capsid core. The molecular architectures of HIV-1 IN assemblies that mediate these distinct events remain unknown. Furthermore, the tetramer is an important antiviral target for allosteric IN inhibitors. Here, we determined cryo-EM structures of wildtype HIV-1 IN tetramers and intasome hexadecamers. Our structures unveil a remarkable plasticity that leverages IN C-terminal domains and abutting linkers to assemble functionally distinct oligomeric forms. Alteration of a newly recognized conserved interface revealed that both IN functions track with tetramerization in vitro and during HIV-1 infection. Collectively, our findings reveal how IN plasticity orchestrates its diverse molecular functions, suggest a working model for IN-viral RNA binding, and provide atomic blueprints for allosteric IN inhibitor development.

biochemistry↗

bioRxiv2024

GVRP: Genome Variant Refinement Pipeline for variant analysis in non-human species using machine learning

Many investigations of human disease require model systems such as non-human primates and their associated genome analyses. While DeepVariant excels in calling human genetic variations, its reliance on calibrating against known variants from previous population studies poses challenges for non-human species. To address this limitation, we introduce the Genome Variant Refinement Pipeline (GVRP), employing a machine learning-based approach to refine variant calls in non-human species. Rather than training separate variant callers for each species, we employ a machine learning model to accurately identify variations and filter out false positives from DeepVariant. In GVRP, we omit certain DeepVariant preprocessing steps and leverage the ground-truth Genome In A Bottle (GIAB) variant calls to train the machine learning model for non-human species genome variant refinement. We anticipate that GVRP will significantly expedite genome variation studies for non-human species.

bioinformatics↗

bioRxiv2024

Hunting for peptide binders of specific targets with data-centric generative language models

Bioactive peptides have become strong candidates for a variety of clinical therapies due to their diverse advantages, which promotes the development of deep generative models for peptide design. Considering that existing methods cannot effectively deal with the conformational flexibility of peptides and are difficult to capture accurate residue-to-residue interaction dependencies, we propose a unified weakly order-dependent autoregressive language modeling architecture (PepGenWOA) for bioactive peptide generative design with tolerating out-of-order input as inductive bias. The superiority of PepGenWOA is demonstrated by generating three classes of therapeutic peptides, including antimicrobial peptides, anticancer peptides, and peptide binders. For antimicrobial and anticancer peptide generation, PepGenWOA not only comprehensively outperforms state-of-the-art baseline models, but also exhibits a significant propensity to incorporate specific types of residues that are beneficial for antimicrobial or anticancer bioactivity. For characteristic-guided peptide binder generation, the pretrained PepGenWOA is fine-tuned with Mixture-of-Experts-style plugins with lifelong learning paradigm, thereby achieving the best trade-off between memory stability for world knowledge and learning plasticity for new downstream tasks. The subsequent structure-based virtual screening anchors the 7 most promising candidates from the mega-scale synthetic sequence space, reducing the number of candidates for in vitro experimental validation by 5 orders of magnitude. A target binding rate of 28.6% with binding specificity further confirms the effectiveness of the fine-tuning strategy. Overall, PepGenWOA is a unified architecture for peptide generative design that can be flexibly customized for different task requirements, thereby harnessing generative language models to reach the "dark space" of biological language.

bioinformatics↗

bioRxiv2023

Semantical and Topological Protein Encoding Toward Enhanced Bioactivity and Thermostability

Protein engineering is a pivotal aspect of synthetic biology, involving the modification of amino acids within existing protein sequences to achieve novel or enhanced functionalities and physical properties. Accurate prediction of protein variant effects requires a thorough understanding of protein sequence, structure, and function. Deep learning methods have demonstrated remarkable performance in guiding protein modification for improved functionality. However, existing approaches predominantly rely on protein sequences, which face challenges in efficiently encoding the geometric aspects of amino acids local environment and often fall short in capturing crucial details related to protein folding stability, internal molecular interactions, and bio-functions. Furthermore, there lacks a fundamental evaluation for developed methods in predicting protein thermostability, although it is a key physical property that is frequently investigated in practice. To address these challenges, this paper introduces a novel pre-training framework that integrates sequential and geometric encoders for protein primary and tertiary structures. This framework guides mutation directions toward desired traits by simulating natural selection on wild-type proteins and evaluates variant effects based on their fitness to perform specific functions. We assess the proposed approach using three benchmarks comprising over 300 deep mutational scanning assays. The prediction results showcase exceptional performance across extensive experiments when compared to other zero-shot learning methods, all while maintaining a minimal cost in terms of trainable parameters. This study not only proposes an effective framework for more accurate and comprehensive predictions to facilitate efficient protein engineering, but also enhances the in silico assessment system for future deep learning models to better align with empirical requirements. The PyTorch implementation are available at https://github.com/tyang816/ProtSSN.

bioengineering↗

bioRxiv2023

Enhanced surface accessibility of SARS-CoV-2 Omicron spike protein due to an altered glycosylation profile

SARS-CoV-2 spike (S) proteins undergo extensive glycosylation, aiding proper folding, enhancing stability, and evading host immune surveillance. In this study, we used mass spectrometric analysis to elucidate the N-glycosylation characteristics and disulfide bonding of recombinant spike proteins derived from the SARS-CoV-2 Omicron variant (B.1.1.529) in comparison with the D614G spike variant. Furthermore, we conducted microsecond-long molecular dynamics simulations on spike proteins to resolve how the different N-glycans impact spike conformational sampling in the two variants. Our findings reveal that the Omicron spike protein maintains an overall resemblance to the D614G spike variant in terms of site-specific glycan processing and disulfide bond formation. Nonetheless, alterations in glycans were observed at certain N-glycosylation sites. These changes, in synergy with mutations within the Omicron spike protein, result in increased surface accessibility of the macromolecule, including ectodomain, receptor-binding domain, and N-terminal domain. These insights contribute to our understanding of the interplay between structure and function, thereby advancing effective vaccination and therapeutic strategies. TeaserThrough mass spectrometry and molecular dynamics simulations, SARS-CoV-2 Omicron spike is found to be less covered by glycans when compared to the D614G spike variant.

molecular biology↗